UNet-rootMUSIC: A High Accuracy Direction of Arrival Estimation Method under Array Imperfection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25547526%3A_____%2F23%3AN0000003" target="_blank" >RIV/25547526:_____/23:N0000003 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/abs/pii/S143484112300482X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/S143484112300482X?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.aeue.2023.155008" target="_blank" >10.1016/j.aeue.2023.155008</a>

Result language

angličtina

Original language name

UNet-rootMUSIC: A High Accuracy Direction of Arrival Estimation Method under Array Imperfection

Original language description

In the practical direction-finding systems, the accuracy and resolution of the direction of arrival (DOA) estimation are affected not only by the Gaussian noise and array size but also by hardware configuration imperfections, such as errors in element manufacturing and mounting. These impairments cause phase and amplitude errors in estimating the DOA of signal sources. To address this issue, this paper proposes to combine a U-shape deep neural network (UNet) with the multiple signal classification via the root of the polynomial (rootMUSIC) algorithm (so-called UNet-rootMUSIC) to improve the DOA estimation accuracy. In this approach, the UNet model plays a role in converting a covariance matrix of received signals containing phase and gain errors into a nearly perfect one of the ideal antenna array. The rootMUSIC algorithm is then employed to estimate the signal DOA based on the converted covariance matrix. The DOA estimation performance of the uniform linear array of eight elements with an inter-element distance of is analyzed through experimental simulations. The simulation results demonstrate that our method can significantly reduce the root mean square error of DOA estimation compared to the conventional MUSIC, rootMUSIC, ESPRIT methods and two deep neural network-based angular classification methods.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

20202 - Communication engineering and systems

Project

<a href="/en/project/TM02000035" target="_blank" >TM02000035: NEO classification of signals (NEOCLASSIG) for radio surveillance systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

C - Předmět řešení projektu podléhá obchodnímu tajemství (§ 504 Občanského zákoníku), ale název projektu, cíle projektu a u ukončeného nebo zastaveného projektu zhodnocení výsledku řešení projektu (údaje P03, P04, P15, P19, P29, PN8) dodané do CEP, jsou upraveny tak, aby byly zveřejnitelné.

Name of the periodical

UNet-rootMUSIC: A High Accuracy Direction of Arrival Estimation Method under Array Imperfection

ISSN

1434-8411

e-ISSN

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Volume of the periodical

Volume 173

Issue of the periodical within the volume

2024-01 | Journal article

Country of publishing house

VN - VIET NAM

Number of pages

5

Pages from-to

334 - 338

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85120580975